EasyABC: Efficient Approximate Bayesian Computation Sampling Schemes

Enables launching a series of simulations of a computer code from the R session, and to retrieve the simulation outputs in an appropriate format for post-processing treatments. Five sequential sampling schemes and three coupled-to-MCMC schemes are implemented.

Version: 1.5
Depends: R (≥ 2.14.0), abc
Imports: pls, mnormt, MASS, parallel, lhs, tensorA
Published: 2015-09-02
Author: Franck Jabot, Thierry Faure, Nicolas Dumoulin, Carlo Albert.
Maintainer: Nicolas Dumoulin <nicolas.dumoulin at irstea.fr>
License: GPL-3
URL: http://easyabc.r-forge.r-project.org/
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: EasyABC results


Reference manual: EasyABC.pdf
Vignettes: EasyABC: a R package to perform efficient approximate Bayesian computation sampling schemes
Package source: EasyABC_1.5.tar.gz
Windows binaries: r-devel: EasyABC_1.5.zip, r-release: EasyABC_1.5.zip, r-oldrel: EasyABC_1.5.zip
OS X El Capitan binaries: r-release: EasyABC_1.5.tgz
OS X Mavericks binaries: r-oldrel: EasyABC_1.5.tgz
Old sources: EasyABC archive


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